Master Thesis Data-Efficient Hybrid Machine Learning for Robust Vibration System Prediction
Share
Job Location:
Monthly Salary:
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
Do you want to bring artificial intelligence into technical applications In collaboration with a team of engineers and scientists you will investigate how to develop more robust and reliable predictive models for technical systems. You will work on enhancing a machine-learning toolbox to forecast vibration-loaded systems and add crucial capabilities to learn from real-world insights especially when measurement data is scarce.
- During your thesis you will research and apply advanced machine learning techniques to integrate limited measurement data into the training of models that currently rely predominantly on simulation data.
- You will develop a benchmark by integrating simulated data and new measurement data from a test bench utilizing machine learning algorithms to predict the dynamic behavior of nonlinear coupled vibration systems.
- Furthermore you will apply and evaluate your chosen approaches comparing their model performance (accuracy and robustness) against simulation-only trained models.
- Finally you will openly communicate your ideas and contributions benefiting from the exchange with colleagues within your team experts in the field and a broader network across various domains and locations within the company.
Qualifications :
- Education: Master studies in the field of Engineering Mathematics Physics Computer Science or comparable with good grades
- Experience and Knowledge: very good knowledge of Python (Pytorch Pandas Numpy etc.); good to very good knowledge of fundamental machine learning concepts and algorithms particularly relevant for regression; good understanding of dynamics / mechanics
- Personality and Working Practice: you excel at driving innovation with a high degree of self-motivation working independently while communicating your progress and ideas effectively
- Work Routine: your on-site presence is required
- Languages: fluent in English and basic in German or fluent in German and very good in English
Additional Information :
Start: according to prior agreement
Duration: 6 months
Requirement for this thesis is the enrollment at university. Please attach your CV transcript of records examination regulations and if indicated a valid work and residence permit.
Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore we welcome all applications regardless of gender age disability religion ethnic origin or sexual identity.
Need further information about the job
Annika Hayn (Functional Department)
30652
Work #LikeABosch starts here: Apply now!
#LI-DNI
Remote Work :
No
Employment Type :
Full-time
Key Skills
About Company
Bosch first started in Vietnam with a representative office in 1994. Bosch has its main office in Ho Chi Minh City, with branch offices in Hanoi and Da Nang, and a Powertrain Solutions plant in the Dong Nai province to manufacture pushbelt for continuously variable transmissions (CVT) ... View more
